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Quantifying human mobility resilience to extreme events using geo-located social media data

Author(s)
Roy, Kamol Chandra; Cebrian, Manuel; Hasan, Samiul
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Abstract
Mobility is one of the fundamental requirements of human life with significant societal impacts including productivity, economy, social wellbeing, adaptation to a changing climate, and so on. Although human movements follow specific patterns during normal periods, there are limited studies on how such patterns change due to extreme events. To quantify the impacts of an extreme event to human movements, we introduce the concept of mobility resilience which is defined as the ability of a mobility system to manage shocks and return to a steady state in response to an extreme event. We present a method to detect extreme events from geo-located movement data and to measure mobility resilience and transient loss of resilience due to those events. Applying this method, we measure resilience metrics from geo-located social media data for multiple types of disasters occurred all over the world. Quantifying mobility resilience may help us to assess the higher-order socio-economic impacts of extreme events and guide policies towards developing resilient infrastructures as well as a nation’s overall disaster resilience strategies.
Date issued
2019-05
URI
https://hdl.handle.net/1721.1/126443
Department
Massachusetts Institute of Technology. Media Laboratory
Journal
EPJ Data Science
Publisher
Springer Science and Business Media LLC
Citation
Roy, Kamol Chandra et al. "Quantifying human mobility resilience to extreme events using geo-located social media data." EPJ Data Science 8, 1 (May 2019): 18 © 2019 Springer Nature
Version: Final published version
ISSN
2193-1127

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